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571 lines
17 KiB
C++
571 lines
17 KiB
C++
////////////////////////////////////////////////////////////////////////////////
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///
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/// Beats-per-minute (BPM) detection routine.
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///
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/// The beat detection algorithm works as follows:
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/// - Use function 'inputSamples' to input a chunks of samples to the class for
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/// analysis. It's a good idea to enter a large sound file or stream in smallish
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/// chunks of around few kilosamples in order not to extinguish too much RAM memory.
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/// - Inputted sound data is decimated to approx 500 Hz to reduce calculation burden,
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/// which is basically ok as low (bass) frequencies mostly determine the beat rate.
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/// Simple averaging is used for anti-alias filtering because the resulting signal
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/// quality isn't of that high importance.
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/// - Decimated sound data is enveloped, i.e. the amplitude shape is detected by
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/// taking absolute value that's smoothed by sliding average. Signal levels that
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/// are below a couple of times the general RMS amplitude level are cut away to
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/// leave only notable peaks there.
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/// - Repeating sound patterns (e.g. beats) are detected by calculating short-term
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/// autocorrelation function of the enveloped signal.
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/// - After whole sound data file has been analyzed as above, the bpm level is
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/// detected by function 'getBpm' that finds the highest peak of the autocorrelation
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/// function, calculates it's precise location and converts this reading to bpm's.
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///
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/// Author : Copyright (c) Olli Parviainen
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/// Author e-mail : oparviai 'at' iki.fi
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/// SoundTouch WWW: http://www.surina.net/soundtouch
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///
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////////////////////////////////////////////////////////////////////////////////
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//
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// License :
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//
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// SoundTouch audio processing library
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// Copyright (c) Olli Parviainen
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//
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// This library is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 2.1 of the License, or (at your option) any later version.
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//
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// This library is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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// Lesser General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License along with this library; if not, write to the Free Software
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// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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//
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////////////////////////////////////////////////////////////////////////////////
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#define _USE_MATH_DEFINES
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#include <math.h>
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#include <assert.h>
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#include <string.h>
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#include <stdio.h>
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#include "FIFOSampleBuffer.h"
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#include "PeakFinder.h"
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#include "BPMDetect.h"
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using namespace soundtouch;
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// algorithm input sample block size
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static const int INPUT_BLOCK_SIZE = 2048;
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// decimated sample block size
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static const int DECIMATED_BLOCK_SIZE = 256;
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/// Target sample rate after decimation
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static const int TARGET_SRATE = 1000;
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/// XCorr update sequence size, update in about 200msec chunks
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static const int XCORR_UPDATE_SEQUENCE = (int)(TARGET_SRATE / 5);
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/// Moving average N size
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static const int MOVING_AVERAGE_N = 15;
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/// XCorr decay time constant, decay to half in 30 seconds
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/// If it's desired to have the system adapt quicker to beat rate
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/// changes within a continuing music stream, then the
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/// 'xcorr_decay_time_constant' value can be reduced, yet that
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/// can increase possibility of glitches in bpm detection.
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static const double XCORR_DECAY_TIME_CONSTANT = 30.0;
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/// Data overlap factor for beat detection algorithm
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static const int OVERLAP_FACTOR = 4;
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static const double TWOPI = (2 * M_PI);
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////////////////////////////////////////////////////////////////////////////////
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// Enable following define to create bpm analysis file:
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//#define _CREATE_BPM_DEBUG_FILE
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#ifdef _CREATE_BPM_DEBUG_FILE
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static void _SaveDebugData(const char *name, const float *data, int minpos, int maxpos, double coeff)
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{
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FILE *fptr = fopen(name, "wt");
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int i;
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if (fptr)
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{
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printf("\nWriting BPM debug data into file %s\n", name);
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for (i = minpos; i < maxpos; i ++)
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{
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fprintf(fptr, "%d\t%.1lf\t%f\n", i, coeff / (double)i, data[i]);
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}
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fclose(fptr);
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}
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}
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void _SaveDebugBeatPos(const char *name, const std::vector<BEAT> &beats)
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{
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printf("\nWriting beat detections data into file %s\n", name);
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FILE *fptr = fopen(name, "wt");
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if (fptr)
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{
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for (uint i = 0; i < beats.size(); i++)
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{
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BEAT b = beats[i];
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fprintf(fptr, "%lf\t%lf\n", b.pos, b.strength);
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}
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fclose(fptr);
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}
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}
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#else
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#define _SaveDebugData(name, a,b,c,d)
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#define _SaveDebugBeatPos(name, b)
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#endif
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// Hamming window
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void hamming(float *w, int N)
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{
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for (int i = 0; i < N; i++)
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{
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w[i] = (float)(0.54 - 0.46 * cos(TWOPI * i / (N - 1)));
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}
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}
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////////////////////////////////////////////////////////////////////////////////
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//
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// IIR2_filter - 2nd order IIR filter
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IIR2_filter::IIR2_filter(const double *lpf_coeffs)
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{
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memcpy(coeffs, lpf_coeffs, 5 * sizeof(double));
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memset(prev, 0, sizeof(prev));
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}
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float IIR2_filter::update(float x)
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{
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prev[0] = x;
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double y = x * coeffs[0];
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for (int i = 4; i >= 1; i--)
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{
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y += coeffs[i] * prev[i];
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prev[i] = prev[i - 1];
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}
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prev[3] = y;
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return (float)y;
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}
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// IIR low-pass filter coefficients, calculated with matlab/octave cheby2(2,40,0.05)
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const double _LPF_coeffs[5] = { 0.00996655391939, -0.01944529148401, 0.00996655391939, 1.96867605796247, -0.96916387431724 };
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////////////////////////////////////////////////////////////////////////////////
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BPMDetect::BPMDetect(int numChannels, int aSampleRate) :
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beat_lpf(_LPF_coeffs)
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{
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beats.reserve(250); // initial reservation to prevent frequent reallocation
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this->sampleRate = aSampleRate;
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this->channels = numChannels;
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decimateSum = 0;
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decimateCount = 0;
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// choose decimation factor so that result is approx. 1000 Hz
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decimateBy = sampleRate / TARGET_SRATE;
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assert(decimateBy > 0);
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assert(INPUT_BLOCK_SIZE < decimateBy * DECIMATED_BLOCK_SIZE);
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// Calculate window length & starting item according to desired min & max bpms
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windowLen = (60 * sampleRate) / (decimateBy * MIN_BPM);
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windowStart = (60 * sampleRate) / (decimateBy * MAX_BPM_RANGE);
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assert(windowLen > windowStart);
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// allocate new working objects
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xcorr = new float[windowLen];
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memset(xcorr, 0, windowLen * sizeof(float));
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pos = 0;
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peakPos = 0;
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peakVal = 0;
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init_scaler = 1;
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beatcorr_ringbuffpos = 0;
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beatcorr_ringbuff = new float[windowLen];
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memset(beatcorr_ringbuff, 0, windowLen * sizeof(float));
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// allocate processing buffer
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buffer = new FIFOSampleBuffer();
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// we do processing in mono mode
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buffer->setChannels(1);
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buffer->clear();
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// calculate hamming windows
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hamw = new float[XCORR_UPDATE_SEQUENCE];
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hamming(hamw, XCORR_UPDATE_SEQUENCE);
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hamw2 = new float[XCORR_UPDATE_SEQUENCE / 2];
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hamming(hamw2, XCORR_UPDATE_SEQUENCE / 2);
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}
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BPMDetect::~BPMDetect()
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{
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delete[] xcorr;
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delete[] beatcorr_ringbuff;
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delete[] hamw;
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delete[] hamw2;
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delete buffer;
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}
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/// convert to mono, low-pass filter & decimate to about 500 Hz.
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/// return number of outputted samples.
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///
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/// Decimation is used to remove the unnecessary frequencies and thus to reduce
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/// the amount of data needed to be processed as calculating autocorrelation
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/// function is a very-very heavy operation.
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///
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/// Anti-alias filtering is done simply by averaging the samples. This is really a
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/// poor-man's anti-alias filtering, but it's not so critical in this kind of application
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/// (it'd also be difficult to design a high-quality filter with steep cut-off at very
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/// narrow band)
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int BPMDetect::decimate(SAMPLETYPE *dest, const SAMPLETYPE *src, int numsamples)
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{
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int count, outcount;
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LONG_SAMPLETYPE out;
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assert(channels > 0);
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assert(decimateBy > 0);
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outcount = 0;
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for (count = 0; count < numsamples; count ++)
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{
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int j;
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// convert to mono and accumulate
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for (j = 0; j < channels; j ++)
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{
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decimateSum += src[j];
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}
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src += j;
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decimateCount ++;
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if (decimateCount >= decimateBy)
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{
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// Store every Nth sample only
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out = (LONG_SAMPLETYPE)(decimateSum / (decimateBy * channels));
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decimateSum = 0;
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decimateCount = 0;
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#ifdef SOUNDTOUCH_INTEGER_SAMPLES
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// check ranges for sure (shouldn't actually be necessary)
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if (out > 32767)
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{
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out = 32767;
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}
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else if (out < -32768)
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{
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out = -32768;
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}
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#endif // SOUNDTOUCH_INTEGER_SAMPLES
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dest[outcount] = (SAMPLETYPE)out;
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outcount ++;
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}
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}
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return outcount;
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}
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// Calculates autocorrelation function of the sample history buffer
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void BPMDetect::updateXCorr(int process_samples)
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{
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int offs;
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SAMPLETYPE *pBuffer;
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assert(buffer->numSamples() >= (uint)(process_samples + windowLen));
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assert(process_samples == XCORR_UPDATE_SEQUENCE);
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pBuffer = buffer->ptrBegin();
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// calculate decay factor for xcorr filtering
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float xcorr_decay = (float)pow(0.5, 1.0 / (XCORR_DECAY_TIME_CONSTANT * TARGET_SRATE / process_samples));
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// prescale pbuffer
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float tmp[XCORR_UPDATE_SEQUENCE];
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for (int i = 0; i < process_samples; i++)
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{
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tmp[i] = hamw[i] * hamw[i] * pBuffer[i];
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}
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#pragma omp parallel for
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for (offs = windowStart; offs < windowLen; offs ++)
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{
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double sum;
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int i;
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sum = 0;
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for (i = 0; i < process_samples; i ++)
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{
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sum += tmp[i] * pBuffer[i + offs]; // scaling the sub-result shouldn't be necessary
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}
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xcorr[offs] *= xcorr_decay; // decay 'xcorr' here with suitable time constant.
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xcorr[offs] += (float)fabs(sum);
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}
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}
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// Detect individual beat positions
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void BPMDetect::updateBeatPos(int process_samples)
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{
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SAMPLETYPE *pBuffer;
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assert(buffer->numSamples() >= (uint)(process_samples + windowLen));
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pBuffer = buffer->ptrBegin();
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assert(process_samples == XCORR_UPDATE_SEQUENCE / 2);
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// static double thr = 0.0003;
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double posScale = (double)this->decimateBy / (double)this->sampleRate;
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int resetDur = (int)(0.12 / posScale + 0.5);
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double corrScale = 1.0 / (double)(windowLen - windowStart);
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// prescale pbuffer
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float tmp[XCORR_UPDATE_SEQUENCE / 2];
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for (int i = 0; i < process_samples; i++)
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{
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tmp[i] = hamw2[i] * hamw2[i] * pBuffer[i];
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}
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#pragma omp parallel for
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for (int offs = windowStart; offs < windowLen; offs++)
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{
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double sum = 0;
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for (int i = 0; i < process_samples; i++)
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{
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sum += tmp[i] * pBuffer[offs + i];
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}
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beatcorr_ringbuff[(beatcorr_ringbuffpos + offs) % windowLen] += (float)((sum > 0) ? sum : 0); // accumulate only positive correlations
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}
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int skipstep = XCORR_UPDATE_SEQUENCE / OVERLAP_FACTOR;
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// compensate empty buffer at beginning by scaling coefficient
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float scale = (float)windowLen / (float)(skipstep * init_scaler);
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if (scale > 1.0f)
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{
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init_scaler++;
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}
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else
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{
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scale = 1.0f;
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}
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// detect beats
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for (int i = 0; i < skipstep; i++)
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{
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LONG_SAMPLETYPE max = 0;
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float sum = beatcorr_ringbuff[beatcorr_ringbuffpos];
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sum -= beat_lpf.update(sum);
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if (sum > peakVal)
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{
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// found new local largest value
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peakVal = sum;
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peakPos = pos;
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}
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if (pos > peakPos + resetDur)
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{
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// largest value not updated for 200msec => accept as beat
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peakPos += skipstep;
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if (peakVal > 0)
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{
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// add detected beat to end of "beats" vector
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beats.push_back({ (float)(peakPos * posScale), (float)(peakVal * scale) });
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}
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peakVal = 0;
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peakPos = pos;
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}
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beatcorr_ringbuff[beatcorr_ringbuffpos] = 0;
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pos++;
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beatcorr_ringbuffpos = (beatcorr_ringbuffpos + 1) % windowLen;
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}
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}
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#define max(x,y) ((x) > (y) ? (x) : (y))
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void BPMDetect::inputSamples(const SAMPLETYPE *samples, int numSamples)
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{
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SAMPLETYPE decimated[DECIMATED_BLOCK_SIZE];
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// iterate so that max INPUT_BLOCK_SAMPLES processed per iteration
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while (numSamples > 0)
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{
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int block;
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int decSamples;
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block = (numSamples > INPUT_BLOCK_SIZE) ? INPUT_BLOCK_SIZE : numSamples;
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// decimate. note that converts to mono at the same time
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decSamples = decimate(decimated, samples, block);
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samples += block * channels;
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numSamples -= block;
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buffer->putSamples(decimated, decSamples);
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}
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// when the buffer has enough samples for processing...
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int req = max(windowLen + XCORR_UPDATE_SEQUENCE, 2 * XCORR_UPDATE_SEQUENCE);
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while ((int)buffer->numSamples() >= req)
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{
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// ... update autocorrelations...
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updateXCorr(XCORR_UPDATE_SEQUENCE);
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// ...update beat position calculation...
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updateBeatPos(XCORR_UPDATE_SEQUENCE / 2);
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// ... and remove proceessed samples from the buffer
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int n = XCORR_UPDATE_SEQUENCE / OVERLAP_FACTOR;
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buffer->receiveSamples(n);
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}
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}
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void BPMDetect::removeBias()
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{
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int i;
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// Remove linear bias: calculate linear regression coefficient
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// 1. calc mean of 'xcorr' and 'i'
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double mean_i = 0;
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double mean_x = 0;
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for (i = windowStart; i < windowLen; i++)
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{
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mean_x += xcorr[i];
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}
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mean_x /= (windowLen - windowStart);
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mean_i = 0.5 * (windowLen - 1 + windowStart);
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// 2. calculate linear regression coefficient
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double b = 0;
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double div = 0;
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for (i = windowStart; i < windowLen; i++)
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{
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double xt = xcorr[i] - mean_x;
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double xi = i - mean_i;
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b += xt * xi;
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div += xi * xi;
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}
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b /= div;
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// subtract linear regression and resolve min. value bias
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float minval = FLT_MAX; // arbitrary large number
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for (i = windowStart; i < windowLen; i ++)
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{
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xcorr[i] -= (float)(b * i);
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if (xcorr[i] < minval)
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{
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minval = xcorr[i];
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}
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}
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// subtract min.value
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for (i = windowStart; i < windowLen; i ++)
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{
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xcorr[i] -= minval;
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}
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}
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// Calculate N-point moving average for "source" values
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void MAFilter(float *dest, const float *source, int start, int end, int N)
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{
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for (int i = start; i < end; i++)
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{
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int i1 = i - N / 2;
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int i2 = i + N / 2 + 1;
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if (i1 < start) i1 = start;
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if (i2 > end) i2 = end;
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double sum = 0;
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for (int j = i1; j < i2; j ++)
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{
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sum += source[j];
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}
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dest[i] = (float)(sum / (i2 - i1));
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}
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}
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float BPMDetect::getBpm()
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{
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double peakPos;
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double coeff;
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PeakFinder peakFinder;
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// remove bias from xcorr data
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removeBias();
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coeff = 60.0 * ((double)sampleRate / (double)decimateBy);
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// save bpm debug data if debug data writing enabled
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_SaveDebugData("soundtouch-bpm-xcorr.txt", xcorr, windowStart, windowLen, coeff);
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// Smoothen by N-point moving-average
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float *data = new float[windowLen];
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memset(data, 0, sizeof(float) * windowLen);
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MAFilter(data, xcorr, windowStart, windowLen, MOVING_AVERAGE_N);
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// find peak position
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peakPos = peakFinder.detectPeak(data, windowStart, windowLen);
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// save bpm debug data if debug data writing enabled
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_SaveDebugData("soundtouch-bpm-smoothed.txt", data, windowStart, windowLen, coeff);
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|
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delete[] data;
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|
|
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assert(decimateBy != 0);
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if (peakPos < 1e-9) return 0.0; // detection failed.
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|
|
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_SaveDebugBeatPos("soundtouch-detected-beats.txt", beats);
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|
|
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// calculate BPM
|
|
float bpm = (float)(coeff / peakPos);
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return (bpm >= MIN_BPM && bpm <= MAX_BPM_VALID) ? bpm : 0;
|
|
}
|
|
|
|
|
|
/// Get beat position arrays. Note: The array includes also really low beat detection values
|
|
/// in absence of clear strong beats. Consumer may wish to filter low values away.
|
|
/// - "pos" receive array of beat positions
|
|
/// - "values" receive array of beat detection strengths
|
|
/// - max_num indicates max.size of "pos" and "values" array.
|
|
///
|
|
/// You can query a suitable array sized by calling this with NULL in "pos" & "values".
|
|
///
|
|
/// \return number of beats in the arrays.
|
|
int BPMDetect::getBeats(float *pos, float *values, int max_num)
|
|
{
|
|
int num = beats.size();
|
|
if ((!pos) || (!values)) return num; // pos or values NULL, return just size
|
|
|
|
for (int i = 0; (i < num) && (i < max_num); i++)
|
|
{
|
|
pos[i] = beats[i].pos;
|
|
values[i] = beats[i].strength;
|
|
}
|
|
return num;
|
|
}
|